Project: Finance Transformation - Oracle Retail Sales Audit (ReSA) Integration. This program is a legacy modernization project in which the client is transforming from main-frame based legacy systems to Oracle Applications. As a part of this transformation, Legacy sales Audit is moved from mainframe-DB2 based system to the Oracle ReSA. The finance data from Oracle ReSA is extracted, transformed and loaded to the multiple interfaces residing in Mainframe DB2, SQL server, Unix AIX, Windows servers using Informatica 9.1, Teradata SQL Assistant 7.0 and UNIX

Environment: Informatica PowerCenter 9.1, Power Exchange, Oracle 10g, SQL developer, Teradata SQL Assistant, Teradata Manager PL/SQL, Unix ReSA .

Responsibilities:

• Involved in deriving Technical Specifications based on Functional Specifications, Process Analysis, Project management, Coding and testing coordination
• Prepared the design and related technical documents including Mapping specification documents and Source to target mapping documents
• Create AS-IS, TO-BE system diagram Estimation, Program Design
• Performed data analysis and gathered columns metadata of source systems for understanding requirement feasibility analysis
• Code changes, testing, Test plan review, Code Reviews
• Wrote several Teradata SQL Queries using Teradata SQL Assistant for Ad Hoc Data Pull re-quest
• Developed and tested ETL components using Informatica Power Center
• Unit/peer testing of developed components
• Worked on Informatica Designer tools like Source Analyzer, Target Designer, Transformation Developer, Mapping Designer and Mapplet Designer
• Involved in creating Tasks, Sessions, Workflows and Worklet by using the Workflow Manager tools like Task Developer, Worklets and Workflow Designer
• Worked with mapping parameters and variables to load data from different sources to corresponding database table
• Worked with Flat Files and XML
• Working with Power Center versioning maintaining the history of objects
• Used Teradata utilities fastload, multiload to load data
• Worked on Teradata SQL Assistant querying the source/target tables to validate the BTEQ scripts
• Analyzed business requirements and worked closely with the various application teams and business teams to develop ETL procedures that are consistent across all applications and systems
• Made substantial contributions in simplifying the development and maintenance of ETL by creating re-usable Source, Target, Mapplets and Transformation objects
• Created worklets to control the execution of various sessions
• Prepared Workflow process to run Worklets, Sessions based on Load dependency

Enabled Coca-Cola to connect to Facebook followers and be able to grow the brand advocacy using Hadoop platform. Leveraged Point of Sales data from companies like Wal-Mart to build customer profiles and enabled collaborative planning, forecasting and replenishment process within their supply chain using all data at hand. Standardized all data through a series of master data management processes and helped Coca-Cola's goal to become efficient and effective within their stores to drive sales and improve the consumer experience

Environment: Hadoop, MapReduce, HDFS, Hive, Pig, Java, SQL, Cloudera Manager, Sqoop, Flume, Oozie, Java (jdk 1.6), Eclipse

Responsibilities:

• Responsible for building scalable distributed data solutions using Hadoop
• Installed and configured Hive, Pig, Sqoop, Flume and Oozie on the Hadoop cluster
• Setup and benchmarked Hadoop/HBase clusters for internal use
• Developed Simple to complex Map/reduce Jobs using Hive and Pig
• Optimized Map/Reduce Jobs to use HDFS efficiently by using various compression mechanisms
• Handled importing of data from various data sources, performed transformations using Hive, MapReduce, loaded data into HDFS and Extracted the data from MySQL into HDFS using Sqoop
• Analyzed the data by performing Hive queries and running Pig scripts to study customer behavior
• Used UDF's to implement business logic in Hadoop
• Implemented business logic by writing UDFs in Java and used various UDFs from Piggybanks and other sources.
• Continuous monitoring and managing the Hadoop cluster using Cloudera Manager
• Worked with application teams to install operating system, Hadoop updates, patches, version upgrades as required
• Installed Oozie workflow engine to run multiple Hive and Pig jobs
• Exported the analyzed data to the relational databases using Sqoop for visualization and to generate reports for the BI team

Description: AT&T is an American multinational telecommunication corporation. It is the largest provider for both mobile and landline telephone service, and also provides broadband subscription television services. Being one of the largest telecommunication providers AT&T has huge customer data that can be analyzed and taken advantage of. To consumer marketing professionals, data about the users of mobile network are highly valuable so that the US-based network operator is turning access to and collaboration on its data into a new business service. In order to ensure secure data sharing and at the same time easing access and use of data, good management of data is required which involves data aggregation from multiple sources. AT&T has created programmable interfaces to each of its data sets that ensure read-only access to the data.

Environment: Hadoop, MapReduce, HDFS, Hive, Pig, Java, SQL, Cloudera Manager, Sqoop, Flume, Oozie, Java (jdk 1.6), Eclipse

Responsibilities:

• Responsible for building scalable distributed data solutions using Hadoop
• Installed and configured Hive, Pig, Sqoop, Flume and Oozie on the Hadoop cluster
• Setup and benchmarked Hadoop/HBase clusters for internal use
• Developed Simple to complex Map/reduce Jobs using Hive and Pig
• Optimized Map/Reduce Jobs to use HDFS efficiently by using various compression mechanisms
• Handled importing of data from various data sources, performed transformations using Hive, MapReduce, loaded data into HDFS and Extracted the data from MySQL into HDFS using Sqoop
• Analyzed the data by performing Hive queries and running Pig scripts to study customer behavior
• Used UDF's to implement business logic in Hadoop
• Implemented business logic by writing UDFs in Java and used various UDFs from Piggybanks and other sources.
• Continuous monitoring and managing the Hadoop cluster using Cloudera Manager
• Worked with application teams to install operating system, Hadoop updates, patches, version upgrades as required
• Installed Oozie workflow engine to run multiple Hive and Pig jobs
• Exported the analyzed data to the relational databases using Sqoop for visualization and to generate reports for the BI team

J.C. Penney Company Inc., is a chain of American mid-range department stores based in Plano, Texas, a suburb north of Dallas. The company operates 1,093 department stores in 49 of the 50 U.S. states (except Hawaii) and Puerto Rico and 6 stores in JC Penney Mexico which are controlled by Mexican capital. J. C. Penney operates by stores, online and Catalog sales merchant offices nationwide in many small markets.

Project: DataMart development for Executive Dashboard

• Executive Dashboard provides key metrics of sales, pricing and traffic for the top level executives at company level, division level and regional level.
• The objective of this project is to build data mart by extracting data from various systems and integrating traffic information with them.
• Traffic information will be provided by third party companies like Shopper Track and IBM Coremetrics where secured paths should be established.
• Designed datamart to report the flash sales and flash traffic information.

Environment: UNIX Shell scripting, Informatica PowerCenter Client 9.1, SVN, DB2

Project: Enterprise Data Warehouse (EDW)

The Enterprise requires weekly Demand through Gross Sales, Gross Profit and Inventory information at the subdivision/item/SKU level for the direct channel. During this phase of project the EDW (Enterprise Data Warehouse) will focus primarily on three work streams: Demand, Inventory, Gross Profit and the population of data into the EDW at the lowest level of granularity. Provide daily/weekly/month-to-date/year-to-date, this year and previous year actual data with drilldown capability for the Demand, Alternate Sales, Omissions and Cancelations.

Environment: UNIX Shell scripting, Informatica PowerCenter Client 9.1, SVN, DB2

Key Responsibilities / Achievements:

• Populate foundation data within the EDW in order to support weekly downstream data requirements
• Leverage contributions of the DSAS (Direct Sales Accounting System) project
• Provide the infrastructure for reporting.
• Build reconciliation mechanism to ensure no discrepancy in data from source and target systems.
• Involve in building the strategy to Implement Customer and transaction level data warehouse on db2.
• Document user requirements and translate requirements into system solutions.
• Architect Star & Snowflake based logical & physical data models for Data Warehouse systems using data modeling tools such as Erwin.
• Involve in creating the functional specification documents for ETL interfaces.
• Design, develop, deploy and support integration processes across the enterprise by utilizing Informatica V9.1
• Develop test plans, test cases, test scripts and test validation data sets for Data Mart, Data Warehouse integration/ETL processes.
• Perform software testing including Unit Testing, Functional Testing, Database Testing, Load Testing, Performance Testing, and User Accepting Testing.
• Provide platform for testing team to perform White/Black Box Testing, System Testing, Regression Testing, Integration Testing, End to End Testing.
• Design and Implement ETL processes for History load and Incremental loads of EDW, Customer and Transaction level data warehouse.
• Document all the interface processes in current data warehouse system and translate them into new ETL processes using Informatica.
• Involve in Data Assessment to identify key data sources and run the system extracts and queries.
• Perform Data cleansing activities to improve the data quality.
• Automate all the new ETL jobs using UNIX shell scripts and add data validation checks including business rules and referential integrity checks.
• Create dimension and fact tables in db2 and perform data bulk loads.
• Perform troubleshooting, performance tuning and performance monitoring for enhancement of jobs.
• Maintain warehouse metadata, naming standards and warehouse standards for future application development.
• Provide support in post-deployment phase and involve in project transition to production support.
• Train production support team to support the application.